Predicting Solar Radiation in Urban Areas Using Morphological Variables
Description
This dataset encompasses a collection of morphological measurements, potentially suitable for prdicting solar radiation in architectural design, urban planning, or related fields of study. Each entry in the dataset represents a set of spatial coordinates along with various environmental and geometrical attributes. Features: X point coordinate: The X-axis coordinate of a point in a defined coordinate system. Y point coordinate: The Y-axis coordinate of a point in the same coordinate system. Z point coordinate: The elevation or Z-axis coordinates, providing a three-dimensional position. Azimuth Angel: The azimuth angle of the point, which may represent orientation or direction relative to a fixed point or axis. Average Height: The mean height calculated from multiple measurements or observations at the given point. Occupied Area: The area that is occupied, possibly referring to structures, vegetation, or other physical entities. Unoccupied Area: The area that is not occupied, which could be open land, water bodies, or spaces without structures. Mean SR: Mean hour solar radiation per year. Data Collection Method: The dataset is likely compiled through systematic measurements using Remote Sensing data, 3D model simulation, analysing energy in Ladybog and Honeybee. However, the specifics of the data collection process are not described here and should be look at the paper which published titled "Predicting Solar Radiation in the Urban Area: A Data-Driven Analysis for Sustainable City Planning Using Artificial Neural Networking ". Intended Use: This data can be used for a variety of purposes, such as Urban planning, urban design, architectural engineering, and analysis of land use patterns, or as training data for machine learning models focused on spatial recognition or classification tasks. Dataset Size: The size of the dataset is 1,012,798 rows and 7 columns in one table with 72 megabit of observations. Users are advised to refer to the dataset directly to understand the scope and scale of the data provided. Accessibility: The dataset is intended for public access and use. However, users are responsible for ensuring that any applications of the data comply with relevant data use policies and respect privacy and ethical considerations.